Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics Research Articles

Ionospheric Response to Solar EUV Radiation Variations Using GOLD Observations and the CTIPe Model

AbstractTo understand the global response of thermospheric‐ionospheric (TI) parameters to variations in solar irradiance measurements from the Global‐Scale Observations of the Limb and Disk (GOLD) ultraviolet imaging spectrograph, solar radio flux F10.7, predictions from the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model, and International Global Navigation Satellite System Service total electron content maps (TEC) have been used. Various parameters such as GOLD O/N2, O2, and the nighttime peak electron density (Nmax) have been compared with the CTIPe model simulations. The GOLD observed Nmax shows a number of significant features including a winter anomaly and an equatorial ionization anomaly. The comparison with solar proxies showed that the GOLD QEUV correlates very well with the EUV observations compared to the F10.7 index. The study also examined the relationship between the solar proxies and Nmax on different time scales and found that Nmax responded significantly to QEUV at both medium‐ and long‐term timescales. Furthermore, a low correlation between Nmax in the equatorial region and solar proxies was found. A delayed ionospheric TEC response against solar flux variations within the 27‐day solar rotation was investigated. This ionospheric delay of TEC with respect to solar flux was observed to be less than 1 day, which was reproduced in model simulations. The current study has shown that the GOLD observations can be used to investigate the delayed ionospheric response and to gain a better understanding of the influence of solar activity on the TI system.

Validation of Ionospheric Specifications During Geomagnetic Storms: TEC and foF2 During the 2013 March Storm Event‐II

AbstractAssessing space weather modeling capability is a key element in improving existing models and developing new ones. In order to track improvement of the models and investigate impacts of forcing, from the lower atmosphere below and from the magnetosphere above, on the performance of ionosphere‐thermosphere models, we expand our previous assessment for 2013 March storm event (Shim et al., 2018, https://doi.org/10.1029/2018SW002034). In this study, we evaluate new simulations from upgraded models (the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model version 4.1 and the Global Ionosphere Thermosphere Model (GITM) version 21.11) and from the NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM‐X) version 2.2 including eight simulations in the previous study. A simulation from the NCAR Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model version 2 (TIE‐GCM 2.0) is also included for comparison with WACCM‐X. TEC and foF2 changes from quiet‐time background are considered to evaluate the model performance on the storm impacts. For evaluation, we employ four skill scores: Correlation coefficient (CC), root‐mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (Yield), and timing error (TE). It is found that the models tend to underestimate the storm‐time enhancements of foF2 (F2‐layer critical frequency) and TEC (Total Electron Content) and to predict foF2 and/or TEC better in North America but worse in the Southern Hemisphere. The ensemble simulation for TEC is comparable to results from a data assimilation model (Utah State University‐Global Assimilation of Ionospheric Measurements (USU‐GAIM)) with differences in skill score less than 3% and 6% for CC and RMSE, respectively.

Improving estimates of the ionosphere during geomagnetic storm conditions through assimilation of thermospheric mass density

Dynamical changes in the ionosphere and thermosphere during geomagnetic storm times can have a significant impact on our communication and navigation applications, as well as satellite orbit determination and prediction activities. Because of the complex electrodynamics coupling processes during storms, which cannot be fully described with the sparse set of thermosphere–ionosphere (TI) observations, it is crucial to accurately model the state of the TI system. The approximation closest to the true state can be obtained by assimilating relevant measurements into physics-based models. Thermospheric mass density (TMD) derived from satellite measurements is ideal to improve the thermosphere through data assimilation. Given the coupled nature of the TI system, the changes in the thermosphere will also influence the ionosphere state. This study presents a quantification of the changes and improvement of the model state produced by assimilating TMD not only for the thermosphere density but also for the ionosphere electron density under storm conditions. TMD estimates derived from a single Swarm satellite and the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) physics-based model are used for the data assimilation. The results are presented for a case study during the St. Patricks Day storm 2015. It is shown that the TMD data assimilation generates an improvement of the model’s thermosphere density of up to 40% (measured along the orbit of the non-assimilated Swarm satellites). The model’s electron density during the course of the storm has been improved by approximately 8 and 22% relative to Swarm-A and GRACE, respectively. The comparison of the model’s global electron density against a high-quality 3D electron density model, generated through assimilation of total electron content, shows that TMD assimilation modifies the model’s ionosphere state positively and negatively during storm time. The major improvement areas are the mid-low latitudes during the storm’s recovery phase.Graphical

Delayed ionospheric response to solar extreme ultraviolet radiation variations: A modeling approach

The behavior of the ionosphere is strongly dependent on solar activity conditions. Attempts have been made to understand the delayed response of the ionosphere at low and high solar activity in a systematic way. The total electron content provided by International GNSS Service (IGS) and Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) was used to study the delay during 2008 and 2013 at the location 50 ° N, 18 ° E. The comparative study shows that the model successfully reproduces the ionospheric behavior during low and high solar activity. In addition, the CTIPe has been used for sensitivity studies with different model components. The analysis suggests that the model reproduction of the ionospheric time delay is significantly affected by various processes such as diffusion, photodissociation, solar and geomagnetic activities. To this end, several model runs were performed during low and high solar activity conditions. Furthermore, we have systematically studied the delayed response of the ionosphere during low, medium, and high solar activity and it was confirmed that the ionospheric delay increases with increasing solar activity.

Storm time neutral density assimilation in the thermosphere ionosphere with TIDA

To improve Thermosphere–Ionosphere modeling during disturbed conditions, data assimilation schemes that can account for the large and fast-moving gradients moving through the modeled domain are necessary. We argue that this requires a physics based background model with a non-stationary covariance. An added benefit of using physics-based models would be improved forecasting capability over largely persistence-based forecasts of empirical models. As a reference implementation, we have developed an ensemble Kalman Filter (enKF) software called Thermosphere Ionosphere Data Assimilation (TIDA) using the physics-based Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model as the background. In this paper, we present detailed results from experiments during the 2003 Halloween Storm, 27–31 October 2003, under very disturbed (Kp = 9) conditions while assimilating GRACE-A and B, and CHAMP neutral density measurements. TIDA simulates this disturbed period without using the L1 solar wind measurements, which were contaminated by solar energetic protons, by estimating the model drivers from the density measurements. We also briefly present statistical results for two additional storms: September 27 – October 2, 2002, and July 26 – 30, 2004, to show that the improvement in assimilated neutral density specification is not an artifact of the corrupted forcing observations during the 2003 Halloween Storm. By showing statistical results from assimilating one satellite at a time, we show that TIDA produces a coherent global specification for neutral density throughout the storm – a critical capability in calculating satellite drag and debris collision avoidance for space traffic management.

Middle and low latitudes hemispheric asymmetries in ∑O/N2 and TEC during intense magnetic storms of solar cycle 24

We have investigated the global hemispheric differences in thermospheric ∑O/N 2 and its impact on the ionospheric total electron content (TEC) at mid- and low-latitudes. Four intense storms of solar cycle 24 (SC-24) have been considered, three of them occurred in Spring equinox and one in Summer solstice season. It is found that the mid-latitudes region has exhibited a large decrease in ∑O/N 2 during all the phases of the storms under consideration, which corresponds well to the observed negative storm effects. This decrease is directly related with the storm intensity. The maximum reduction in the ∑O/N 2 is observed for the St. Patrick day storm of 2015 (which was the most intense geomagnetic storm of SC-24), whereas the respective minimum decrease is found for the storm of April 2012. Strong hemispheric asymmetries, in ∑O/N 2 variation, have been observed at the mid-latitudes sector, and can be associated with the asymmetric energy input as indicated by polar cap (PC) indices. The high speed solar winds streams (HSSWs) during the recovery phases of March 2013 and 2015 storms have caused a significant reduction in ∑O/N 2 at mid-latitudes, which could not be reproduced by the coupled thermosphere-ionosphere-plasmasphere electrodynamics (CTIPe) model. On the other hand the low-latitudes region depicts an enhancement in ∑O/N 2 during all the storms except for the early recovery phases. The positive storm effect at low-latitudes agrees well with this ∑O/N 2 increase, thus indicating that the composition change is one of the major drivers of TEC enhancement at low-latitudes. The CTIPe model showed discrepancies in reproducing the satellite data for all the considered storms, especially during the recovery phases. Furthermore, the model is failed to replicate the hemispheric asymmetries at low and mid-latitudes during the main and early recovery phases.

Thermospheric Neutral Winds as the Cause of Drift Shell Distortion in Earth’s Inner Radiation Belt

Recent analysis of energetic electron measurements from the Magnetic Electron Ion Spectrometer instruments onboard the Van Allen Probes showed a local time variation of the equatorial electron intensity in the Earth’s inner radiation belt. The local time asymmetry was interpreted as evidence of drift shell distortion by a large-scale electric field. It was also demonstrated that the inclusion of a simple dawn-to-dusk electric field model improved the agreement between observations and theoretical expectations. Yet, exactly what drives this electric field was left unexplained. We combine in-situ field and particle observations, together with a physics-based coupled model, the Rice Convection Model (RCM) Coupled Thermosphere-Ionosphere-Plasmasphere-electrodynamics (CTIPe), to revisit the local time asymmetry of the equatorial electron intensity observed in the innermost radiation belt. The study is based on the dawn-dusk difference in equatorial electron intensity measured at L = 1.30 during the first 60 days of the year 2014. Analysis of measured equatorial electron intensity in the 150–400 keV energy range, in-situ DC electric field measurements and wind dynamo modeling outputs provide consistent estimates of the order of 6–8 kV for the average dawn-to-dusk electric potential variation. This suggests that the dynamo electric fields produced by tidal motion of upper atmospheric winds flowing across Earth’s magnetic field lines - the quiet time ionospheric wind dynamo - are the main drivers of the drift shell distortion in the Earth’s inner radiation belt.

Role of eddy diffusion in the delayed ionospheric response to solar flux changes

Abstract. Simulations of the ionospheric response to solar flux changes driven by the 27 d solar rotation have been performed using the global 3-D Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) physics-based numerical model. Using the F10.7 index as a proxy for solar extreme ultraviolet (EUV) variations in the model, the ionospheric delay at the solar rotation period is well reproduced and amounts to about 1 d, which is consistent with satellite and in situ measurements. From mechanistic CTIPe studies with reduced and increased eddy diffusion, we conclude that the eddy diffusion is an important factor that influences the delay of the ionospheric total electron content (TEC). We observed that the peak response time of the atomic oxygen to molecular nitrogen ratio to the solar EUV flux changes quickly during the increased eddy diffusion compared with weaker eddy diffusion. These results suggest that an increase in the eddy diffusion leads to faster transport processes and an increased loss rate, resulting in a decrease in the ionospheric time delay. Furthermore, we found that an increase in solar activity leads to an enhanced ionospheric delay. At low latitudes, the influence of solar activity is stronger because EUV radiation drives ionization processes that lead to compositional changes. Therefore, the combined effect of eddy diffusion and solar activity leads to a longer delay in the low-latitude and midlatitude region.

Ionospheric response to solar extreme ultraviolet radiation variations: comparison based on CTIPe model simulations and satellite measurements

Abstract. The ionospheric total electron content (TEC) provided by the International GNSS Service (IGS) and the TEC simulated by the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model have been used to investigate the delayed ionospheric response against solar flux and its trend during the years 2011 to 2013. The analysis of the distinct low-latitude and midlatitude TEC response over 15∘ E shows a better correlation of observed TEC and the solar radio flux index F10.7 in the Southern Hemisphere compared to the Northern Hemisphere. Thus, a significant hemispheric asymmetry is observed. The ionospheric delay estimated using model-simulated TEC is in good agreement with the delay estimated for observed TEC against the flux measured by the Solar Dynamics Observatory (SDO) extreme ultraviolet (EUV) Variability Experiment (EVE). The average delay for the observed (modeled) TEC is 17(16) h. The average delay calculated for observed and modeled TEC is 1 and 2 h longer in the Southern Hemisphere compared to the Northern Hemisphere. Furthermore, the observed TEC is compared with the modeled TEC simulated using the SOLAR2000 and EUVAC flux models within CTIPe over northern and southern hemispheric grid points. The analysis suggests that TEC simulated using the SOLAR2000 flux model overestimates the observed TEC, which is not the case when using the EUVAC flux model.

Evaluation of Total Electron Content Prediction Using Three Ionosphere‐Thermosphere Models

AbstractPrediction of ionospheric state is a critical space weather problem. We expand on our previous research of medium‐range ionospheric forecasts and present new results on evaluating prediction capabilities of three physics‐based ionosphere‐thermosphere models (Thermosphere Ionosphere Electrodynamics General Circulation Model, TIE‐GCM; Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics Model, CTIPe; and Global Ionosphere Thermosphere Model, GITM). The focus of our study is understanding how current modeling approaches may predict the global ionosphere for geomagnetic storms (as studied through 35 storms during 2000–2016). Prediction approach uses physics‐based modeling without any manual model adjustment, quality control, or selection of the results. Our goal is to understand to what extent current physics‐based modeling can be used in total electron content (TEC) prediction and explore uncertainties of these prediction efforts with multiday lead times. The ionosphere‐thermosphere model runs are driven by actual interplanetary conditions, whether those data come from real‐time measurements or predicted values themselves. These model runs were performed by the Community Coordinated Modeling Center (CCMC). Jet Propulsion Laboratory (JPL)‐produced global ionospheric maps (GIMs) were used to validate model TEC estimates. We utilize the True Skill Statistic (TSS) metric for the TEC prediction evaluation, noting that this is but one metric to assess predictive skill and that complete evaluations require combinations of such metrics. The meanings of contingency table elements for the prediction performance are analyzed in the context of ionosphere modeling. Prediction success is between about 0.2 and 0.5 for weak ionospheric disturbances and decreases for strong disturbances. We evaluate the prediction of TEC decreases and increases. Our results indicate that physics‐based modeling during storms shows promise in TEC prediction with multiday lead time.

On the difference between real-time and research simulations with CTIPe

Understanding the thermosphere and ionosphere conditions is crucial for spacecraft operations and many applications using radio signal transmission (e.g. in communication and navigation). In this sense, physics based modelling plays an important role, since it can adequately reproduce the complex coupling mechanisms in the magnetosphere-ionosphere-thermosphere (MIT) system. The accuracy of the physics based model results does not only depend on the appropriate implementation of the physical processes, but also on the quality of the input data (forcing). In this study, we analyze the impact of input data uncertainties on the model results. We use the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics model (CTIPe), which requires satellite based solar wind, interplanetary field and hemispheric power data from ACE and TIROS/NOAA missions. To identify the impact of the forcing uncertainties, two model runs are compared against each other. The first run uses the input data that were available in real-time (operational) and the second run uses the best estimate obtained in post-processing (research or historical run). The analysis is performed in a case study on the 20th November 2003 extreme geomagnetic storm, that caused significant perturbations in the MIT system. This paper validates the thermosphere and ionosphere response to this storm over Europe comparing both CTIPe model runs with measurements of Total Electron Content (TEC) and thermosphere neutral density. In general, CTIPe results show a good agreement with measurements. However, the deviations between the model and observations are larger in the ionosphere than in the thermosphere. The comparison of the two model runs reveals that the deviations between model results and measurements are larger for the operational run than the research run. It is evident for the storm analyzed here, that data gaps in the input data are impacting considerably the model performance. The consistency between simulation and measurements allows the interpretation of the physical mechanisms behind the ionosphere perturbations and the changes in neutral composition during this event. Joule heating in the Auroral region, generating meridional winds and large scale surges, is suggested to be the main driver of the positive ionospheric storm over central Europe. In the polar cap and Auroral region, convection processes dominate the thermosphere-ionosphere conditions. This study does not only illustrate the importance of working with a good estimate of the model forcing, but also indicates the necessity of using measurements and models, to get a better understanding of the most likely responsible processes for the observed storm effects.

Assessment of Current Capabilities in Modeling the Ionospheric Climatology for Space Weather Applications: foF2 and hmF2

AbstractThis paper presents preliminary results of a metrics‐based assessment of current modeling capabilities in predicting the ionospheric climatology for two ionospheric characteristics, the foF2 and hmF2. This work is part of the activities of the Ionosphere Working Group of the International Forum for Space Weather Modeling Capabilities Assessment that is facilitated by the Community Coordinated Modeling Center. The results are based on the comparison between modeled and observed monthly medians of the foF2 and hmF2. Modeling formulations considered here include two empirical models (the International Reference Ionosphere [IRI] and Massachusetts Institute of Technology [MIT] Empirical model), as well as two physics‐based, coupled ionosphere‐thermosphere models (the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics [CTIPe] and Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model [TIE‐GCM]). The comparisons were carried out in year 2012 over seven ionospheric locations distributed worldwide in the Northern Hemisphere. Based on our findings, although significant errors are occasionally obtained from all modeling approaches, empirical models tend to provide systematically better correlation with the observed medians and follow the observed distributions more successfully, offering smaller prediction errors than the physics‐based ones. In case of foF2, the averaged prediction accuracy in terms of root‐mean‐square error (RMSE) ranges around 1.5 MHz for physics‐based models and 0.5 MHz for empirical models. In case of hmF2, it ranges around 30 and 20 km, respectively. The prediction accuracy presents strong seasonal and local time dependence, which differs for different models and ionospheric characteristics (i.e., foF2 or hmF2): it is strong for physics‐based models, weaker for IRI, and very weak for MIT empirical model. This latter outcome may provide suggestive input for future improvements.

Ionospheric response to solar EUV variations: Preliminary results

Abstract. We investigate the ionospheric response to solar Extreme Ultraviolet (EUV) variations using different proxies, based on solar EUV spectra observed from the Solar Extreme Ultraviolet Experiment (SEE) onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite, the F10.7 index (solar irradiance at 10.7 cm), and the Bremen composite Mg-II index during January 2003 to December 2016. The daily mean solar proxies are compared with global mean Total Electron Content (GTEC) values calculated from global IGS TEC maps. The preliminary analysis shows a significant correlation between GTEC and both the integrated flux from SEE and the Mg II index, while F10.7 correlates less strongly with GTEC. The correlations of EUV proxies and GTEC at different time periods are presented. An ionospheric delay in GTEC is observed at the 27 days solar rotation period with the time scale of about ∼1–2 days. An experiment with the physics based global 3-D Coupled Thermosphere/Ionosphere Plasmasphere electrodynamics (CTIPe) numerical model was performed to reproduce the ionospheric delay. Model simulations were performed for different values of the F10.7 index while keeping all the other model inputs constant. Preliminary results qualitatively reproduce the observed ∼1–2 days delay in GTEC, which is might be due to vertical transport processes.

Occurrence of the dayside three‐peak density structure in the F2 and the topside ionosphere

AbstractIn this work, we discuss the occurrence of the dayside three‐peak electron density structure in the ionosphere. We first use a set of ground‐based and satellite‐borne instruments to demonstrate the development of a large‐amplitude electron density perturbation at the recovery phase of a moderate storm of 11 October 2008. The perturbation developed in the F2 and low topside ionospheric regions over the American sector; it was concentrated on the north from the equatorial ionization anomaly (EIA) but was clearly separated from it. At the F2 region height, the amplitude of the observed perturbation was comparable or even exceeded that of the EIA. Further analysis of the observational data together with the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics model simulation results showed that a particular local combination of the thermospheric wind surges provided favorable conditions for the generation of the three‐peak EIA structure. We further proceed with a statistical study of occurrence of the three‐peak density structure in the ionosphere in general. Based on the analysis of 7 years of the in situ data from CHAMP satellite, we found that such three‐peak density structure occurs sufficiently often during geomagnetically quiet time. The third ionization peak develops in the afternoon hours in the summer hemisphere at solstice periods. Based on analysis of several quiet time events, we conclude that during geomagnetically quiet time, the prevailing summer‐to‐winter thermospheric circulation acts in similar manner as the storm‐time enhanced thermospheric winds, playing the decisive role in generation of the third ionization peak in the daytime ionosphere.

Modeling the ionosphere-thermosphere response to a geomagnetic storm using physics-based magnetospheric energy input: OpenGGCM-CTIM results

The magnetosphere is a major source of energy for the Earth's ionosphere and thermosphere (IT) system. Current IT models drive the upper atmosphere using empirically calculated magnetospheric energy input. Thus, they do not sufficiently capture the storm-time dynamics, particularly at high latitudes. To improve the prediction capability of IT models, a physics-based magnetospheric input is necessary. Here, we use the Open Global General Circulation Model (OpenGGCM) coupled with the Coupled Thermosphere Ionosphere Model (CTIM). OpenGGCM calculates a three-dimensional global magnetosphere and a two-dimensional high-latitude ionosphere by solving resistive magnetohydrodynamic (MHD) equations with solar wind input. CTIM calculates a global thermosphere and a high-latitude ionosphere in three dimensions using realistic magnetospheric inputs from the OpenGGCM. We investigate whether the coupled model improves the storm-time IT responses by simulating a geomagnetic storm that is preceded by a strong solar wind pressure front on August 24, 2005. We compare the OpenGGCM-CTIM results with low-earth-orbit satellite observations and with the model results of Coupled Thermosphere-Ionosphere-Plasmasphere electrodynamics (CTIPe). CTIPe is an up-to-date version of CTIM that incorporates more IT dynamics such as a low-latitude ionosphere and a plasmasphere, but uses empirical magnetospheric input. OpenGGCMCTIM reproduces localized neutral density peaks at approx. 400 km altitude in the high-latitude dayside regions in agreement with in situ observations during the pressure shock and the early phase of the storm. Although CTIPe is in some sense a much superior model than CTIM, it misses these localized enhancements. Unlike the CTIPe empirical input models, OpenGGCM-CTIM more faithfully produces localized increases of both auroral precipitation and ionospheric electric fields near the high-latitude dayside region after the pressure shock and after the storm onset, which in turn effectively heats the thermosphere and causes the neutral density increase at 400 km altitude.

Positive and negative ionospheric storms occurring during the 15 May 2005 geomagnetic superstorm

AbstractThis study focuses on the 15 May 2005 geomagnetic superstorm and aims to investigate the global variation of positive and negative storm phases and their development. Observations are provided by a series of global total electron content maps and multi‐instrument line plots. Coupled Thermosphere‐Ionosphere‐Plasmasphere electrodynamics (CTIPe) simulations are also employed. Results reveal some sunward streaming plumes of storm‐enhanced density (SED) over Asia and a well‐developed midlatitude trough over North America forming isolated positive and negative storms, respectively. The simultaneous development of positive and negative storms over North America is also shown. Then, some enhanced auroral ionizations maintained by strong equatorward neutral winds appeared in the depleted nighttime ionosphere. Meanwhile, the northern nighttime polar region became significantly depleted as the SED plume plasma could not progress further than the dayside cusp. Oppositely, a polar tongue of ionization (TOI) developed in the daytime southern polar region. According to CTIP simulations, solar heating locally maximized (minimized) over the southern (northern) magnetic pole. Furthermore, strong upward surges of molecular‐rich air created O/N2 decreases both in the auroral zone and in the trough region, while some SED‐related downward surges produced O/N2 increases. From these results we conclude for the time period studied that (1) composition changes contributed to the formation of positive and negative storms, (2) strengthening polar convection and increasing solar heating of the polar cap supported polar TOI development, and (3) a weaker polar convection and minimized solar heating of the polar cap aided the depletion of polar plasma.

Lidar and CTIPe model studies of the fast amplitude growth with altitude of the diurnal temperature “tides” in the Antarctic winter lower thermosphere and dependence on geomagnetic activity

AbstractFour years of lidar observations at McMurdo reveal that the fast amplitude growth with altitude of diurnal temperature tides from 100 to 110 km during Antarctic winters, exceeding that of the freely propagating tides from the lower atmosphere, increases in strength with the Kp magnetic activity index. Simulations with the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model reproduce the lidar observations and exhibit concentric ring structures of diurnal amplitudes encircling the south geomagnetic pole and overlapping the auroral zone. These findings point to a magnetospheric source origin. Mechanistic studies using CTIPe show that the adiabatic cooling/heating associated with Hall ion drag is the dominant source of this feature, while Joule heating is a minor contributor due to the counteraction by Joule‐heating‐induced adiabatic cooling. The sum of total dynamical effects and Joule heating explains ~80% of the diurnal amplitudes. Auroral particle heating, lower atmosphere tides, and direct solar heating have minor contributions.

Equatorial westward electrojet impacting equatorial ionization anomaly development during the 6 April 2000 superstorm

AbstractWe investigate the forward plasma fountain and the equatorial ionosphere in the topside region during the 6 April 2000 superstorm in the Australian sector at ~0900 LT. Space‐ and ground‐based multi‐instrument measurements, Coupled Thermosphere‐Ionosphere‐Plasmasphere Electrodynamics (CTIPe) simulations, and field‐aligned observations comprise our results. These reveal an unusual storm development during which the eastward prompt penetration electric (E) field (PPEF) developed and operated under the continuous effects of the westward disturbance dynamo E‐field (DDEF) while large‐scale traveling ionospheric disturbances (TIDs) traveled equatorward and generated strong equatorward wind surges. We have identified the eastward PPEF by the superfountain effect causing the equatorial ionization anomaly (EIA)'s development with crests situated at ~±28°N (geomagnetic) in the topside ionosphere at ~840 km altitude. The westward DDEF's occurrence is confirmed by mapping the “anti‐Sq” current system wherein the equatorial westward current created a weak long‐lasting westward electrojet event. Line plots of vertical drift data tracked large‐scale TIDs. Four scenarios, covering ~3.5 h in universal time, demonstrate that the westward DDEF became superimposed on the eastward PPEF. As these E‐fields of different origins became mapped into the F region, they could interact. Consequently, the eastward PPEF‐related equatorial upward E × B drift became locally reduced by up to 75 m/s near the dip equator by the westward DDEF‐related equatorial downward E × B drift. Meanwhile, the EIA displayed a better development as equatorial wind surges, reproduced by CTIPe, increased from 501 to 629 m/s, demonstrating the crucial role of mechanical wind effects keeping plasma density high.

On the validation effort of the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics model

[1] The Coupled Thermosphere Ionosphere Plasmasphere electrodynamics model (CTIPe) has proven to be a valuable ionospheric research tool. Improving our knowledge of systematic and seasonal model biases is necessary if further improvements are to be made. This paper presents the next step in our verification and validation effort and in developing a standardized analysis methodology. A semi-automated software part of the near-real-time-run of CTIPe is described and results derived from its usage are presented. Model limitations and biases are detailed for the electron density profile peak (NmF2) and its corresponding height (hmF2). Model performance for hmF2 is constant throughout the whole year, with an average 10% deviation from observed values. There is a strong seasonal variation for NmF2, with greater deviations from the observed trends during summer. This effect seems to have latitude dependence, although the gaps in the available data do not allow for an exact determination of its nature.

Data assimilation of thermospheric mass density

Accurate modeling of thermospheric mass density variation is of foremost importance to low Earth orbital prediction. The accuracy of empirical neutral density models based on global indices for solar and geomagnetic activity is inherently limited by the resolution of these indices. Assimilative modeling is appealing, as it provides a means to systematically identify and correct the inconsistencies between model specification and observations. In this paper we present a practical assimilative mass density specification methodology that optimally combines the mass density prediction by the Coupled‐Thermosphere‐Ionosphere‐Plasmasphere‐electrodynamics (CTIPe) model with in‐situ observations of neutral mass density by research satellites such as Challenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE). The methodology yields an analysis of the global density according to Bayes's rule under the assumption of Gaussian prior and observation error distribution (namely, by using the Optimal Interpolation or Kalman Filter update formula). To make best use of under‐sampled global neutral mass density observations, the background (prior) error covariance is built on the principal component analysis to represent the long‐distance correlation effectively, with an adaptive capability by using the maximum‐likelihood method. The neutral mass density specification at 400 km can be improved up to 50% beyond what has been attained by the CTIPe by assimilating CHAMP and GRACE density observations.